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Integrating Object Boundary in Super-Resolution Land-Cover Mapping
Chen, Yuehong1; Ge, Yong1,2; Jia, Yuanxin1
2017
Source PublicationIEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN1939-1404
Volume10Issue:1Pages:219-230
Corresponding AuthorChen, Yuehong(chenyh@lreis.ac.cn)
AbstractThis paper proposes a novel class allocation strategy in units of object (UOO) for soft-then-hard super-resolution mapping (STHSRM). STHSRM involves two processes: 1) subpixel sharpening and 2) class allocation. The UOO is implemented in the second process by integrating the object boundaries as an additional structural constraint. First, UOO obtains the object boundaries from remote-sensing images by image segmentation. The number of subpixels within an object is then calculated for each class to meet the coherence constraint of fractional images imposed by soft classification. Finally, a linear optimization model is built for each object to obtain the optimal hard class labels of subpixels. A synthetic image and two real remote-sensing images are used to evaluate the effectiveness of UOO. The results are compared visually and quantitatively with two existing class allocation methods: 1) the highest attribute values first (HAVF) and 2) units of class (UOC). The experimental results show that UOO performs better than these twomethods. UOO can better reduce the salt and pepper effect in resultant maps than both HAVF and UOC when dealing with real remote-sensing images. Moreover, UOO can better maintain the structure of land-cover patches, with smoother boundaries as compared with the two methods.
KeywordLand cover object boundary remotely sensed imagery super-resolution mapping (SRM)
DOI10.1109/JSTARS.2016.2533571
WOS KeywordREMOTELY-SENSED IMAGERY ; HOPFIELD NEURAL-NETWORK ; SHIFTED HYPERSPECTRAL IMAGERY ; SUB-PIXEL SCALES ; CLASSIFICATION OUTPUT ; SPATIAL DEPENDENCE ; SENSING IMAGERY ; MIXED PIXELS ; MAP MODEL ; INFORMATION
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41471296] ; Key Technologies Research and Development Program of China[2012BAH33B01]
Funding OrganizationNational Natural Science Foundation of China ; Key Technologies Research and Development Program of China
WOS Research AreaEngineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEngineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000391719900020
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/65170
Collection中国科学院地理科学与资源研究所
Corresponding AuthorChen, Yuehong
Affiliation1.Univ Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Chen, Yuehong,Ge, Yong,Jia, Yuanxin. Integrating Object Boundary in Super-Resolution Land-Cover Mapping[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2017,10(1):219-230.
APA Chen, Yuehong,Ge, Yong,&Jia, Yuanxin.(2017).Integrating Object Boundary in Super-Resolution Land-Cover Mapping.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,10(1),219-230.
MLA Chen, Yuehong,et al."Integrating Object Boundary in Super-Resolution Land-Cover Mapping".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 10.1(2017):219-230.
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